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Related papers: Real-Time Detection of Local No-Arbitrage Violatio…

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We are interested in the existence of equivalent martingale measures and the detection of arbitrage opportunities in markets where several multi-asset derivatives are traded simultaneously. More specifically, we consider a financial market…

Pricing of Securities · Quantitative Finance 2021-11-23 Antonis Papapantoleon , Paulo Yanez Sarmiento

A novel method for sequential outlier detection in non-stationary time series is proposed. The method tests the null hypothesis of ``no outlier'' at each time point, addressing the multiple testing problem by bounding the error probability…

Statistics Theory · Mathematics 2025-02-26 Florian Heinrichs , Patrick Bastian , Holger Dette

In this article, we show necessary and sufficient conditions for a function to transform a continuous Markov semimartingale to a semimartingale. As a result, the no-arbitrage principle guarantees the differentiability of asset prices with…

Probability · Mathematics 2025-12-22 Kihun Nam , Yunxi Xu

Based on It\^o semimartingale models, several studies have proposed methods for forecasting intraday volatility using high-frequency financial data. These approaches typically rely on restrictive parametric assumptions and are often…

Econometrics · Economics 2025-07-31 Sung Hoon Choi , Donggyu Kim

Given a stock price process, we analyse the potential of arbitrage by insiders in a context of short-selling prohibitions. We introduce the notion of minimal supermartingale measure, and we analyse its properties in connection to the…

Mathematical Finance · Quantitative Finance 2022-01-13 Delia Coculescu , Aditi Dandapani

In this paper, a general framework is developed for continuous-time financial market models defined from simple strategies through conditional topologies that avoid stochastic calculus and do not necessitate semimartingale models. We then…

Pricing of Securities · Quantitative Finance 2024-05-14 Dorsaf Cherif , Emmanuel Lepinette

We develop a nonparametric test for deciding whether volatility of an asset follows a standard semimartingale process, with paths of finite quadratic variation, or a rough process with paths of infinite quadratic variation. The test…

Statistics Theory · Mathematics 2024-07-16 Carsten H. Chong , Viktor Todorov

The present paper deals with the characterization of no-arbitrage properties of a continuous semimartingale. The first main result, Theorem \refMainTheoremCharNA, extends the no-arbitrage criterion by Levental and Skorohod [Ann. Appl.…

Probability · Mathematics 2008-12-10 Eva Strasser

In this paper we employ deep learning techniques to detect financial asset bubbles by using observed call option prices. The proposed algorithm is widely applicable and model-independent. We test the accuracy of our methodology in numerical…

Mathematical Finance · Quantitative Finance 2024-06-21 Francesca Biagini , Lukas Gonon , Andrea Mazzon , Thilo Meyer-Brandis

The paper develops no arbitrage results for trajectory based models by imposing general constraints on the trading portfolios. The main condition imposed, in order to avoid arbitrage opportunities, is a local continuity requirement on the…

Probability · Mathematics 2015-01-19 Alexander Alvarez , Sebastian Ferrando

Large-scale neutrino observatories operate under unavoidable detector deadtime arising from photomultiplier saturation, digitizer limits, and front-end readout constraints. Conventional coincidence-based trigger logic implicitly assumes…

Instrumentation and Detectors · Physics 2026-01-27 Thammarat Yawisit , Pittaya Pannil

The optimal rate of convergence of estimators of the integrated volatility, for a discontinuous It\^{o} semimartingale sampled at regularly spaced times and over a fixed time interval, has been a long-standing problem, at least when the…

Statistics Theory · Mathematics 2014-06-24 Jean Jacod , Markus Reiss

Training deep learning neural networks often requires massive amounts of computational ressources. We propose to sequentially monitor network predictions to trigger retraining only if the predictions are no longer valid. This can reduce…

Statistics Theory · Mathematics 2026-01-30 Ansgar Steland

We investigate the almost sure asymptotic properties of vector martingale transforms. Assuming some appropriate regularity conditions both on the increasing process and on the moments of the martingale, we prove that normalized moments of…

Probability · Mathematics 2018-12-05 Bernard Bercu , Peggy Cénac , Guy Fayolle

This paper proposes a novel test for simultaneous jumps in a bivariate It\^o semimartingale when observation times are asynchronous and irregular. Inference is built on a realized correlation coefficient for the jumps of the two processes…

Statistics Theory · Mathematics 2016-06-24 Ole Martin , Mathias Vetter

This paper derives the rate of convergence and asymptotic distribution for a class of Kolmogorov-Smirnov style test statistics for conditional moment inequality models for parameters on the boundary of the identified set under general…

Applications · Statistics 2011-12-06 Timothy B. Armstrong

We derive limit theorems for the empirical distribution function of "devolatilized" increments of an It\^{o} semimartingale observed at high frequencies. These "devolatilized" increments are formed by suitably rescaling and truncating the…

Probability · Mathematics 2014-07-03 Viktor Todorov , George Tauchen

We describe a Matlab routine that allows us to estimate the jumps in financial asset prices using the Threshold (or Truncation) method of Mancini (2009). The routine is designed for application to five-minute log-returns. The underlying…

Computational Finance · Quantitative Finance 2025-08-27 Cecilia Mancini

Consider the problem on sequential change-point detection on multiple data streams. We provide the asymptotic lower bounds of the detection delays at all levels of change-point sparsity and we derive a smaller asymptotic lower bound of the…

Statistics Theory · Mathematics 2023-06-02 Jingyan Huang

Sequential change detection is a classical problem with a variety of applications. However, the majority of prior work has been parametric, for example, focusing on exponential families. We develop a fundamentally new and general framework…

Methodology · Statistics 2023-10-31 Jaehyeok Shin , Aaditya Ramdas , Alessandro Rinaldo